The TIMEDATA Procedure (Experimental)

Overview: TIMEDATA Procedure

The TIMEDATA procedure analyzes time-stamped transactional data with respect to time and accumulates the data into a time series format.

After the transactional data are accumulated to form a time series and any missing values are interpreted, the accumulated time series can be functionally transformed using log, square root, logistic, or Box-Cox transformations. The time series can be further transformed using simple differencing, seasonal differencing, or both. After functional and difference transformations have been applied, the accumulated and transformed time series can be stored in an output data set. This working time series can then be analyzed further using various time series analysis techniques provided by this procedure or other SAS/ETS procedures.

The TIMEDATA procedure is very similar to the TIMESERIES procedure. However, unlike the TIMESERIES procedure (which enables you to perform a variety of standard time series analysis techniques), the TIMEDATA procedure enables you to define your own analyses using SAS programming statements.

By default, the TIMEDATA procedure provides no further analyses.

The TIMEDATA procedure forms time series vectors and then provides these vectors as SAS data arrays for subsequent processing by your SAS programming statements. Your programming statements are processed independently for each BY group. The TIMEDATA procedure is like the SAS DATA step for time series data. The SAS DATA step processes data by each row; the TIMEDATA procedure processes time series vectors.

As part of your SAS programming statements, you can include user-defined functions and subroutines created by the FCMP procedure. Additionally, you can use the RUN_MACRO subroutine provided by the FCMP procedure to submit SAS statements that use any SAS procedures.

All results of the transactional or time series analysis can be stored in output data sets or printed using the Output Delivery System (ODS).